Active learning in a real-world bioengineering problem: A pilot-study on ophthalmologic data processing

Dominique Persano Adorno, Leonardo Bellomonte

Risultato della ricerca: Article

Abstract

Active learning is a format alternative to the conventional lecture/recitation/laboratory; research results have reported that it is suitable to encourage studentinquiry and foster peer mentoring. Although the availability of computer-basedlearning materials in biomedical sciences is increasing, there are relatively fewstudies aimed to integrate traditional methods of teaching with inquiry-basedapproaches utilizing these Information and Communication Technologies (ICT)tools. This paper describes a pilot-study on a comprehensive active laboratory courseabout digital ophthalmologic signal classification, experienced by a group ofundergraduates in Bio-Electronic Engineering. During the activity, the studentsbecame able to discriminate healthy subjects from patients affected by two retinalpathologies: Achromatopsia or Congenital Stationary Night Blindness. The studywas based on the analysis and classification of the electroretinograms, that record theretinal response to a light flash. To process electroretinographic data, a software basedon the Empirical Mode Decomposition and an Artificial Neural Network was used.Our findings indicate that this laboratory experience can be considered effective inimproving student's reasoning skills and that students acting as investigators achievea better outcome, presumably because this activity satisfies their psychological needsfor autonomy, competence, and relatedness.
Lingua originaleEnglish
pagine (da-a)485-499
Numero di pagine15
RivistaDefault journal
Volume27
Stato di pubblicazionePublished - 2019

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Education
  • Engineering(all)

Cita questo

@article{260f1b3c35aa490d997b32c2517488ef,
title = "Active learning in a real-world bioengineering problem: A pilot-study on ophthalmologic data processing",
abstract = "Active learning is a format alternative to the conventional lecture/recitation/laboratory; research results have reported that it is suitable to encourage studentinquiry and foster peer mentoring. Although the availability of computer-basedlearning materials in biomedical sciences is increasing, there are relatively fewstudies aimed to integrate traditional methods of teaching with inquiry-basedapproaches utilizing these Information and Communication Technologies (ICT)tools. This paper describes a pilot-study on a comprehensive active laboratory courseabout digital ophthalmologic signal classification, experienced by a group ofundergraduates in Bio-Electronic Engineering. During the activity, the studentsbecame able to discriminate healthy subjects from patients affected by two retinalpathologies: Achromatopsia or Congenital Stationary Night Blindness. The studywas based on the analysis and classification of the electroretinograms, that record theretinal response to a light flash. To process electroretinographic data, a software basedon the Empirical Mode Decomposition and an Artificial Neural Network was used.Our findings indicate that this laboratory experience can be considered effective inimproving student's reasoning skills and that students acting as investigators achievea better outcome, presumably because this activity satisfies their psychological needsfor autonomy, competence, and relatedness.",
author = "{Persano Adorno}, Dominique and Leonardo Bellomonte",
year = "2019",
language = "English",
volume = "27",
pages = "485--499",
journal = "Default journal",

}

TY - JOUR

T1 - Active learning in a real-world bioengineering problem: A pilot-study on ophthalmologic data processing

AU - Persano Adorno, Dominique

AU - Bellomonte, Leonardo

PY - 2019

Y1 - 2019

N2 - Active learning is a format alternative to the conventional lecture/recitation/laboratory; research results have reported that it is suitable to encourage studentinquiry and foster peer mentoring. Although the availability of computer-basedlearning materials in biomedical sciences is increasing, there are relatively fewstudies aimed to integrate traditional methods of teaching with inquiry-basedapproaches utilizing these Information and Communication Technologies (ICT)tools. This paper describes a pilot-study on a comprehensive active laboratory courseabout digital ophthalmologic signal classification, experienced by a group ofundergraduates in Bio-Electronic Engineering. During the activity, the studentsbecame able to discriminate healthy subjects from patients affected by two retinalpathologies: Achromatopsia or Congenital Stationary Night Blindness. The studywas based on the analysis and classification of the electroretinograms, that record theretinal response to a light flash. To process electroretinographic data, a software basedon the Empirical Mode Decomposition and an Artificial Neural Network was used.Our findings indicate that this laboratory experience can be considered effective inimproving student's reasoning skills and that students acting as investigators achievea better outcome, presumably because this activity satisfies their psychological needsfor autonomy, competence, and relatedness.

AB - Active learning is a format alternative to the conventional lecture/recitation/laboratory; research results have reported that it is suitable to encourage studentinquiry and foster peer mentoring. Although the availability of computer-basedlearning materials in biomedical sciences is increasing, there are relatively fewstudies aimed to integrate traditional methods of teaching with inquiry-basedapproaches utilizing these Information and Communication Technologies (ICT)tools. This paper describes a pilot-study on a comprehensive active laboratory courseabout digital ophthalmologic signal classification, experienced by a group ofundergraduates in Bio-Electronic Engineering. During the activity, the studentsbecame able to discriminate healthy subjects from patients affected by two retinalpathologies: Achromatopsia or Congenital Stationary Night Blindness. The studywas based on the analysis and classification of the electroretinograms, that record theretinal response to a light flash. To process electroretinographic data, a software basedon the Empirical Mode Decomposition and an Artificial Neural Network was used.Our findings indicate that this laboratory experience can be considered effective inimproving student's reasoning skills and that students acting as investigators achievea better outcome, presumably because this activity satisfies their psychological needsfor autonomy, competence, and relatedness.

UR - http://hdl.handle.net/10447/349454

UR - https://onlinelibrary.wiley.com/doi/10.1002/cae.22091

M3 - Article

VL - 27

SP - 485

EP - 499

JO - Default journal

JF - Default journal

ER -